Founded in 1856, Banque Internationale à Luxembourg (BIL) is the oldest multi-business bank in the Grand Duchy. It has always played an active role in the main stages of development of the Luxembourg economy. It currently operates in retail, private and corporate banking, as well as on financial markets. Employing more than 2,000 people, BIL is present in the financial centres of Luxembourg, Switzerland, Denmark, and China.
As a member of the Advanced Analytics & Big data team, you will apply statistical and quantitative approaches in a growing scope of applications, such as:
· Financial markets predictions
· Financial incomes optimization
· Risk monitoring automation
· AML KYC/KYT compliance
· Internal processes efficiency
· Data quality improvement
And more globally, contribute to make BIL to become a data driven organization, by identifying proactively new business cases to tackle with Data Science.
The transversal scope of Advanced Analytics & Big data team involves a collaboration with a wide range of BIL services and profiles. More than being a technical position, this role requires to understand business stakes and to be able to propose the best way to tackle problems (including new ones if needed). In consequence, a both business orientation and solution-oriented mindset is mandatory.
As a data scientist, your day-to-day job will consist to:
· Explore available data, to identify the best sources for models
· Create new insights or new models, applying different statistical algorithms (supervised or non-supervised exercises) and choosing the most adapted to each business issue
· Test model results, in close collaboration with sales forces and business supports, and deploy them for action when validated
· Work closely with IT for industrialization, with BI Services for integration of data insights into reports, and Data Governance for enhancing Data Quality Management on Analytics outcomes
· Leverage on Analytics Capabilities (Cluster Big Data with Spark) when it is relevant
· Keep an observation activity about new methods, technologies, market trends in AI and Data Science (Machine Learning, Big Data, Deep Learning & Neural Networks, NLP…). Contribute to the “Lab” (or “R&D”) mindset of the team
· Strong statistical & mathematical background (e.g. ENSAI/ENSAE engineer)
· +5 years of work experience, preferably as a data scientist or in highly technical and analytical role, within a financial institution (e.g. Risk Management) or in a consulting firm
· General knowledge of banking products. Knowledge of AML Compliance would be an asset.
· Hands-on experience in working with large datasets/data warehouses, using data mining and modeling tools and languages (Python highly preferred)
· Practical experience on Hadoop ecosystem (with Spark) would be a strong asset
· Strong interest in new technologies, especially in Data Science & AI
· In-depth knowledge on statistical modeling and predictive analytics (theory and practice): Machine Learning, Deep Learning, NLP, Anomaly detection
· Strong communication and presentation skills to share findings and to explain complex statistical concepts to a non-technical audience
· Experience in Project Management would be an asset
· Willing to combine a job with business and highly technical aspects
· Knowledge in Business Intelligence tools & concepts (proven experience of an advanced Data visualization tool, such as Micro Strategy, is an advantage)
· Strong appetence for figures, statistics, algorithmic and quantitative activities
· Client oriented, ability to understand business problems and appetence to have a real impact on them
· Able to organize him/herself and set priorities
· Willing to learn (technologies, methods) and to develop his own expertise
· Team player
BIL offers a broad range of challenging projects and a huge choice of career paths - we will assist you in finding the one that best meets your skills and expectations. Your personal development is our priority and we greatly encourage you to take on roles in different business areas for the broadest possible experience.